Predicting Corporate Financial Distress: A Time-Series CUSUM Methodology
by Emel Kahya of Rutgers University, and
Abstract: This paper develops a financial distress model using the statistical methodology of time-series Cumulative Sums (CUSUM). The model has the ability to distinguish between changes in the financial variables of a firm that are the result of serial correlation and changes that are the result of permanent shifts in the mean structure of the variables due to financial distress. Tests performed show that the CUSUM model is robust over time and outperforms other models based on the popular statistical methods of Linear Discriminant Analysis and Logit.
Published in: Review of Quantitative Finance and Accounting, Vol. 13, No. 4, (December 1999), pp. 323-345.